The present invention relates to a channel estimation device, and in particular relates to a channel estimation device in wireless communication in which a plurality of subcarriers are used for communication.
In wireless communication, transmission signals pass through a plurality of channels to arrive at a receiver. Consequently the signals observed by the receiver are waveforms with amplitude and phase distorted by multipath fading. As means of correcting such distortion, synchronous detection (channel compensation) using a pilot signal is employed. In a system which adopts the synchronous detection, a pilot signal is transmitted from a transmitter, and at a receiver the pilot signal is used to estimate multipath fading channel, and the channel estimation values are used in synchronous detection to demodulate data. At this time, if the error in channel estimation values is large, the result of data demodulation is affected, causing an increase in the data error rate.
On the other hand, in recent years numerous communication systems have used OFDM (Orthogonal Frequency Division Multiplexing), a characteristic of which is a high frequency utilization efficiency. OFDM (including OFDMA) is a multicarrier transmission method, which employs a plurality of orthogonal subcarriers, mapping transmission data onto the subcarriers for transmission. Normally, pilot signals are mapped onto a plurality of subcarriers similarly to data. As explained above, in synchronous detection these pilot signals are used to determine channel estimation values for each subcarrier, and the channel estimation values are employed to perform data demodulation.
FIG. 21 shows the configuration of a transmission device in an OFDM communication system; the data modulation portion 1 performs, for example, QPSK data modulation of transmission data including user data and control data), and converts the data to complex baseband signals referred to as symbols having an in-phase component and a quadrature component. The time-division multiplexing portion 2 performs time-division multiplexing of a plurality of pilot symbols into data symbols. The serial/parallel conversion portion 3 converts input data into N-symbol parallel data, and outputs N subcarrier samples. The IFFT (Inverse Fast Fourier Transform) portion 4 performs IFFT processing of N subcarrier samples input in parallel and merging the results for output as discrete-time signals (OFDM signal). The guard interval insertion portion 5 inserts guard intervals into the N-symbol portion of OFDM signals input from the IFFT portion, and the transmission portion (TX) 6 performs DA conversion of the OFDM signals with guard intervals inserted, converts the OFDM signal frequency from the baseband to the radio frequency band, performs high-frequency amplification, and transmits the signals from the antenna 7.
FIG. 22 shows the configuration of an OFDM reception device. Signals output from a transmission antenna 7 pass through a fading channel and are received by the reception antenna 8 of the reception device; the reception circuit (Rx) 9 converts the RF signals received by the antenna into baseband signals, and the baseband signals are AD converted into digital signals and output. The FFT timing synchronization circuit 10 detects the FFT timing of the time-domain signals output from the reception circuit 9, and the symbol extraction portion 11 deletes the GI and extracts OFDM symbols from the time-domain signals based on the FFT timing, and inputs the OFDM symbols to the FFT portion 12. The FFT portion 12 performs FFT processing for each extracted OFDM symbol consisted of N samples, converting this symbol into frequency-domain subcarrier samples S0 to SN-1. The channel estimation circuit 13 calculates the correlation between pilot signals received at fixed intervals and a known pilot pattern to perform channel estimation for each subcarrier, and the synchronous detection circuit (channel compensation circuit) 14 uses the channel estimation values for each subcarrier to perform demodulation of data symbols. By means of the above processing, transmission data distributed into each of the subcarriers is demodulated. Thereafter, the demodulated subcarrier signals, not shown, are converted into serial data and then decoded.
In the above explanation, it is assumed that the number of subcarriers for data mapping, the number of IFFT points, and the number of FFT points are equal; but in actuality, the number of subcarriers for data mapping is smaller than the number of IFFT points and the number of FFT points. The reason for this is as follows.
If N data items are subjected to N-point IFFT processing as components of N subcarriers f1 to fN, then the frequency spectrum is as shown in (A) of FIG. 23. In OFDM, an IFFT-processed signal is analog-converted, and a low-pass filter is used to extract the f1 to fN baseband signal components from the analog signal, which are up-converted to the radio frequency and transmitted. In order to select these f1 to fN baseband signal components, a low-pass filter having a sharp cutoff characteristic is necessary, as is clear in (A) of FIG. 23; fabrication of such a filter is difficult. Hence as shown in (B) of FIG. 23, the carriers on either side of the N subcarriers f1 to fN are not used, that is, Nc subcarriers (Nc<N) are used for data transmission.
In addition to the above-described technique of the prior art, various other methods have been proposed as channel estimation methods used in a channel estimation circuit 13. The first of these methods is a channel estimation method characterized by conversion of a frequency-domain pilot signal into the time domain, followed by noise suppression processing in the time domain, and then reconversion into the frequency domain (see the first and second references: Takashi Dateki et al, “ODFM channel estimation by adding a virtual channel frequency response”, 2006 Nat'l Conv. Rec. IEICE, B-5-94, and J. J. Beek et al, “On channel estimation in OFDM systems”, Proc. 45th IEEE Vehicular Technology Conference, Chicago, Ill., USA, July 1995, pp. 815-819). A second method is a channel estimation method in which the pilot is averaged in the subcarrier direction and time-axis direction and channel estimation is performed for each subcarrier (the third reference: see Kawai et al, “Effect of multi-slot and subcarrier averaging channel estimation filter in QRM-MLD for MIMO multiplexing using OFDCDM”, IEICE Tech. Rep., RCS2004-68, May 2004).
FIG. 24 shows the configuration of a channel estimation device which realizes the above-described first channel estimation method; two channel estimation portions 21, 22 are connected in series. The first channel estimation portion 21 is a channel estimation portion comprising the configuration of the prior art explained in FIG. 22; by calculating the correlation between received pilot signals and a known pilot pattern with a fixed period, channel estimation is performed for each subcarrier. The second channel estimation portion 22 converts the channel estimation values output by the first channel estimation portion 21 into the time domain, performs noise-suppression processing in the time domain, and then returns the signals to the frequency domain and outputs channel estimation values for each subcarrier. That is, the IFFT portion 22a uses IFFT to convert frequency-domain channel estimation values output from the first channel estimation portion 21 into the time domain, the noise-suppression portion 22b eliminates noise at or below a preset level from the time-domain channel estimation values, and the FFT portion 22c returns the noise-suppressed time-domain channel estimation values to the frequency domain and outputs frequency-domain channel estimation values (channel estimation values for each subcarrier). The IFFT and FFT can also be configured using IDFT (Inverse Discrete Fourier Transform) and DFT, or using IDCT (Inverse Discrete Cosine Transform) and DCT.
In the first channel estimation method of the prior art, a constant noise level is suppressed, so that in general the channel estimation values for subcarriers at center of the frequency domain are improved, but the precision of subcarriers at both ends worsens. FIG. 25 shows the MSE (Mean Square Error) for each subcarrier. The MSE is a value obtained by determining the difference between a power of the signal received by way of a known channel h and a power of the signal received by say of an estimated channel h′, and changing the known channel variously to determine a plurality of power differences, which are averaged. As is clear from FIG. 25, the MSE of the subcarriers at both ends is degraded, that is, the channel estimation value is degraded; consequently there is the problem that the data error rates for the subcarriers at both ends are degraded compared with the data error rates for subcarriers near the center. The reason for this is as follows.
Consider the time-domain square wave shown in (A) of FIG. 26. When the Fourier transform of such a square wave is taken, a sinc function is obtained. This sinc function has an infinite interval, and so frequency components extend to infinity. That is, the time-domain square wave can be represented by sine waves of frequencies extending to infinity. However, as shown in (B) of FIG. 26, consider a case in which the sinc function is set to 0 at and above a certain frequency (so that there are only finite frequency components). If after such an approximation an inverse Fourier transform is performed to return to the time domain, the square wave can no longer be accurately represented. In particular, near the points at which the square wave changes rapidly, that is near the points at which the value of the square wave changes from 0 to 1 and from 1 to 0, accurate representation is no longer possible.
In the first channel estimation method of the prior art, time-domain signals are sinc function signals, and in order to suppress noise, the signal is set to 0 at and below a certain threshold. The above-described phenomenon occurs due to this operation, and distortion occurs in subcarriers at both ends of the communication band, so that the MSE is degraded. In the case of the first channel estimation method, the time-domain signals are sinc signals, but the only difference is that t and f in FIG. 26 are interchanged, and the same result is obtained.
By means of the second channel estimation method of the prior art, the influence of noise is eliminated and the S/N ratio is improved, but there is the problem that the noise suppression effect is small.